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The purpose of this paper is to analyze the overall morbidity prevalence and their differentials among emigrants’ and non-emigrants’ wives in Kerala, India.

The study is based on the third round of The Kerala Migration Survey-2007 data. The third round of KMS was perhaps the first survey which has collected data on Indian emigration and morbidity scenario during 2007 at the household and individual level. Descriptive statistics, binary logistic regression models, and Oaxaca decomposition models were used to examine the disease differentials among emigrants’ and non-emigrants’ wives.

The paper shows that household size is negatively associated with chronic disease and incidence of morbidity is much lower among emigrants’ wives. The result also shows that among women, those who stay with a husband or whose husbands are elsewhere in India show a higher incidence of morbidity than those whose husbands are abroad, owing to the limited scope of activity as well as freedom in lifestyle and for taking independent decisions. Thus, it can be concluded that for women, the scope of activity and the freedom to live are important factors contributing to the level of morbidity. Blinder-Oaxaca decomposition results show that non-poor households and non-Muslim religion are in a disadvantageous position in terms of chronic morbidity.

This paper is based on the cross-sectional nature of data; this is an obvious limitation on the effect of emigration on morbidity differentials among emigrants’ and non-emigrants’ wives.

There are few or rare studies conducted so far to investigate the effect of migration on the health of the spouses or families left behind.

Using the latest census data (2010), this paper investigates housing poverty conditions in Shanghai, the largest city in China. The data shows that a large fraction of Shanghai households are still living in excessively over-crowded housing. Meanwhile, the incidence ratio of housing poverty among migrants is more than five times than among natives. In particular, 45% of rural migrant households were living in housing poverty. Poverty decomposition analysis shows that approximately 70% of total housing poverty in Shanghai is attributable to rural migrants. Our finding is supported by estimating the multidimensional poverty index (MPI). The findings in this paper have significant implications to general housing policy making in urban China.

This paper aims to understand housing demand of urban Indian households in terms of housing and household-level characteristics. Because a house is a bundle of certain characteristics which vary across houses, each characteristic has an implicit price. Finding this implicit price for certain important characteristics is the first objective of this study. The second objective of the paper is to compute the income elasticity and price elasticity of housing demand for these cities.

To achieve comparable estimates, household-level data from India’s National Sample Survey Organisation housing surveys for the years 2002 and 2008-2009 have been used. A hedonic price function is estimated using ordinary least squares (OLS) and Box-Cox functional forms to estimate the implicit prices of housing characteristics. This exercise is attempted for owned and rented houses separately. Demand function required for computing the elasticities, uses the hedonic price index derived from the implicit prices and household characteristics.

The study finds housing demand to be income elastic and price inelastic for the six cities across both the time periods.

Firstly, this study includes housing characteristics such as individual access to drinking water, modern sanitation facility, separate kitchen, condition of the structure, existence of a road with street light and whether the house is in a slum or non-slum area in the hedonic price function. These variables were not used in any of the earlier studies pertaining to India. Secondly, it uses the Box-Cox non-linear form to derive the hedonic price function, a specification not used earlier. Thirdly, this is the first study analysing housing demand across the six largest Indian cities.

Cost of living is an important consideration for the decision-making of expatriates and investment decisions of businesses. As competition between cities for talent and capital becomes global instead of national, the need for timely and internationally comparable information on global cities’ cost of living increases. While commercial research houses frequently publish cost of living surveys, these reports can be lacking in terms of scientific rigour. In this context, this paper aims to contribute to the literature by formulating a comprehensive and rigorous methodology to compare the cost of living for expatriates in 103 world’s major cities.

A cost of living index for expatriates composed of the ten consumption categories is constructed. The results from the study covers a study period from 2005 to 2014 in 103 cities. More than 280 individual prices of 165 goods and services have been compiled for each city in the calculation of the cost of living index for expatriates. New York has been chosen as the base city for the study, with other cities being benchmarked against it. A larger cost of living index for expatriates implies that the city is more expensive for expatriates to live in and vice versa.

While the authors generate the cost of living rankings for expatriates for 103 cities worldwide, in this paper, the authors focus on five key cities, namely, London, Hong Kong, Singapore, Tokyo and Zurich, as they are global financial centres. In 2013, the latest year for which data are available, Zurich was the most expensive for expatriates among the five cities, followed by Singapore, Tokyo, London and Hong Kong. These results pertain to the cost of living for expatriates, and cities compare very differently in terms of cost of living for ordinary residents, as ordinary residents follow different consumption patterns from expatriates.

Cost of living in the destination city is a major consideration for professionals who look to relocate, and organisations factor such calculations in their decisions to post employees overseas and design commensurate compensation packages. This paper develops a comprehensive and rigorous methodology for measuring and comparing cost of living for expatriates around the world. The value-addition lies in the fact that the authors are able to differentiate between expatriates and ordinary residents, which has not been done in the existing literature. They use higher quality data and generate an index that is not sensitive to the choice of base city.

By considering the rapid and continuous increase of housing prices in Turkey recently, this study aims to examine the determinants of the residential property price index (RPPI). In this context, a total of 12 explanatory (3 macroeconomic, 8 markets and 1 pandemic) variables are included in the analysis. Moreover, the residential property price index for new dwellings (NRPPI) and the residential property price index for old dwellings (ORPPI) are considered for robustness checks.

A quantile regression (QR) model is used to examine the main determinants of RPPI in Turkey. A monthly time series data set for the period between January 2010 and October 2020 is included. Moreover, NRPPI and ORPPI are examined for robustness.

Predictions for RPPI, NRPPI and ORPPI are carried out separately at the country (Turkey) level. The results show that market variables are more important than macroeconomic variables; the pandemic and rent have the highest effect on the indices; The effects of the explanatory variables on housing prices do not change much from low to high levels, the COVID-19 pandemic and weighted average cost of funding have a decreasing effect on indices while other variables have an increasing effect in low quantiles; the pandemic and monetary policy indicators have a negative and significant effect in low quantiles whereas they are not effective in high quantiles; the results for RPPI, NRPPI and ORPPI are consistent and robust.

The results of the study emphasize the importance of the pandemic, rent, monetary policy indicators and interest rates on the indices, respectively. On the other hand, focusing solely on Turkey and excluding global variables is the main limitation of this study. Therefore, the authors encourage researchers to work on other emerging countries by considering global variables. Hence, future studies may extend this study.

The COVID-19 pandemic and market variables are determined as influential variables on housing prices in Turkey whereas macroeconomic variables are not effective, which does not mean that macroeconomic variables can be fully ignored. Hence, the main priority should be on focusing on market variables by also considering the development in macroeconomic variables.

Emerging countries can make housing prices stable and affordable, which will increase homeownership. Hence, they can benefit from stability in housing markets.

The QR method is performed for the first time to examine housing prices in Turkey at the country level according to the existing literature. The results obtained from the QR analysis and policy implications can also be used by other emerging countries that would like to increase homeownership to provide better living conditions to citizens by making housing prices stable and keeping them under control. Hence, countries can control housing prices and stimulate housing affordability for citizens.

The purpose of this paper is to construct a hedonic property price index in the segmented housing market.

Three different research questions are investigated. The first considers how to identify separate local housing markets, with the use of a regression‐tree approach, and the second concerns when it is possible to update a price index, with a recursive regression approach. Finally, the question about seasonal adjustment is investigated.

Overall, the hedonic approach is the best method to use. Moreover, the County of Stockholm is not one market in the sense that the market can be represented by only one property price index. It can be best described as a number of different sub‐markets where the property prices grow differently. The results suggest that there exist at least five different price indexes in the County of Stockholm. The results also support that recursive regressions are two appropriate methods to answer the research questions. Here, the empirical analysis suggests that the parameter estimates converge relatively fast toward the estimate using all observations.

The paper illustrates how to derive sub‐markets in the construction of a price index and when to update a price index series.

The introduction of new financial products, such as property derivatives, to the market has made the construction and quality of property price indexes more important. High quality price indexes are vital when it comes to, for example, pricing property derivatives. The paper facilitates this.

The elderly seem to be more subject to housing problems due to lower income, older age of the housing stock and lower mobility. Nonetheless, housing deprivation (HD) is commonly analysed amongst the general population. Less is known about the differences between age clusters, which seems to be a crucial issue in countries like Poland due to population ageing. What is more, the current literature usually analyses only the occurrence of HD, while also an accumulation of its indicators seems to be substantial. The aim of this article is to identify the differences in HD (its occurrence and accumulation) amongst elderly and non-elderly households and to diagnose the risk factors behind those phenomena.

The HD index was calculated and compared. Next, the multinomial logit models were used to assess risk factors of HD.

The study showed that, surprisingly, HD in Poland occurs more frequently amongst non-elderly households. The elderly ones suffered more from housing cost overburden, while non-elderly from the overpopulation. In large part, analysed risk factors had a stronger influence on housing conditions of the elderly than non-elderly households.

Social policy tools should focus on the situation of single elderly households, especially living in houses, often in villages. This group is particularly affected by problems with the quality of the dwelling and housing cost overburden.

In the paper, the occurrence and accumulation of HD indicators were analysed. The authors applied a methodological framework that is applicable to other European Union (EU) member states based on the EU Survey on Income and Living Conditions (EU-SILC) data. It is possible to continue the research study and compare different economies.

This paper evaluates consumption-based poverty in the United States using Consumer Expenditure Survey data. The poverty measures rest upon micro-theoretic foundations of utility maximizing behavior and a complete demand system. The Translog model (Christensen et al., 1975) is used to replicate and extend Slesnick’s (1993) measures of poverty into the late 1990s. Consumption-based poverty analysis is extended by computing Sen (1976) indexes, which provide more complete measures of poverty than simple headcount ratios. The robustness of Slesnick’s results is tested under alternative assumptions concerning shares of services between housing and other durables across time.

Rents are both a very important cost variable in the housing market, having large welfare and distributional implication, and one of the most important variables in house price research. The aim of this paper is to construct rent indices for Norway's capital, Oslo.

This paper uses a unique dataset with 24,257 housing for rent advertisements, creating hedonic indices using the time dummy variable method.

In this paper, the author presents annual rent indices for Norway's capital, Oslo, over the period from 1970 to 2008. In addition to an aggregate index, they construct hedonic rent indices for different flat types.

Existing Norwegian rent indices start around 2000 or are constructed with the purpose of being a part of the CPI, and are therefore adjusted for change in quality. Since the author's indices are not adjusted for quality, they give new information about Norwegian rent for the past 40 years.